Formal Methods for Assessing Patient Satisfaction in a Patient-Doctor Relationship

2018 ◽  
pp. 201-219
Author(s):  
Aleksandra Mreła ◽  
Oleksandr Sokołov
Keyword(s):  
Fuzzy Logic ◽  
Patient Satisfaction ◽  
Fuzzy Sets ◽  
Formal Methods ◽  
Classical Logic ◽  
Fuzzy Relations ◽  
The Relationship

When patients visit a doctor, they not only expect to be cured, but also to feel that they are taken care of. The patients like to be treated like guests, sit in a nice place during waiting for a doctor and feel that they are taken care of seriously at the reception desk. All these factors are important for the patients but the relationship with doctors seems to be the most valid. When the patients can choose a clinic where they want to make an appointment with a doctor, the owners and managers of the clinics try to persuade people to choose their clinic. Hence more and more often managers of the clinics try to find out the opinion of the patients, so scientists carried out the research on this phenomenon and called it Patient Satisfaction. This chapter presents the application of fuzzy sets and fuzzy relations to gather and analyze the information from patients and compute their contentment. Using classical logic is less appropriate because the patients can only choose two values: they are satisfied or dissatisfied. Fuzzy logic let the patients choose more phrases for their opinions.

A Fuzzy Logic Trail Finding Algorithm Trained With Human Knowledge

2002 ◽  
Author(s):  
Charles Kinney ◽  
Dean B. Edwards
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Classical Logic ◽  
Fuzzy Logic System ◽  
Human Knowledge ◽  
Relationship Of ◽  
The Relationship ◽  
Logic System

This paper presents a method for developing a fuzzy logic trail finding algorithm using a technique called embedding human knowledge. The trail finding algorithm was trained to find the pixels in images that closely resemble those that were classified as belonging to a forest trail by a human analyst. The relationship of the fuzzy logic system to a classical logic system is discussed as a method for training the fuzzy sets to mimic a human. The results show that the method outlined in this paper reduced the error in the fuzzy logic system by 99%. More generally, this method can be applied to many different situations to find features in images quickly and effectively.

Penerapan Logika Samar dalam Peramalan Data Runtun Waktu

2011 ◽  
Vol 3 (2) ◽  
pp. 11-15
Author(s):  
Seng Hansun
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Time Series Analysis ◽  
Fuzzy Sets ◽  
Fuzzy System ◽  
Time Series Data ◽  
Fuzzy Logic System ◽  
Series Data ◽  
Series Analysis ◽  
Logic System

Recently, there are so many soft computing methods been used in time series analysis. One of these methods is fuzzy logic system. In this paper, we will try to implement fuzzy logic system to predict a non-stationary time series data. The data we use here is Mackey-Glass chaotic time series. We also use MATLAB software to predict the time series data, which have been divided into four groups of input-output pairs. These groups then will be used as the input variables of the fuzzy logic system. There are two scenarios been used in this paper, first is by using seven fuzzy sets, and second is by using fifteen fuzzy sets. The result shows that the fuzzy system with fifteen fuzzy sets give a better forecasting result than the fuzzy system with seven fuzzy sets. Index Terms—forecasting, fuzzy logic, Mackey-Glass chaotic, MATLAB, time series analysis

PELAYANAN PUBLIK KESEHATAN PUSKESMAS DALAM MEMBERIKAN KEPUASAN MASYARAKAT DI KABUPATEN SUMENEP

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Aryo Wibisono ◽  
R. Amilia Destryana
Keyword(s):  
Public Health ◽  
Logistic Regression ◽  
Patient Satisfaction ◽  
Health Center ◽  
Public Service ◽  
Public Health Center ◽  
The Public ◽  
Regression Methods ◽  
Total Satisfaction ◽  
The Relationship

This study aims to determine the index of public satisfaction in public health center services in Sumenep Regency and the relationship between the services to the public satisfaction. The analysis measured the index of public satisfaction and logistic regression methods to determine the effect of the relationship on total satisfaction in the health services of Public Health Center. The results of the study are the alignment between interests and patient satisfaction is still not aligned, there are still differences between interests and satisfaction, the pattern of the result is the relationship between the assurance dimension to the service satisfaction of the public health center, and the results of the index of public satisfaction  values show that the results of the community assess the public health center performance is very good by getting an A grade. Keywords: public service, logistic regretion, index of public satisfaction

scholarly journals Aggregation of Indistinguishability Fuzzy Relations Revisited

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1441
Author(s):  
Juan-De-Dios González-Hedström ◽  
Juan-José Miñana ◽  
Oscar Valero
Keyword(s):  
Equivalence Relation ◽  
Fuzzy Relations ◽  
Measure Of Similarity ◽  
Dual Notion ◽  
The Relationship

Indistinguishability fuzzy relations were introduced with the aim of providing a fuzzy notion of equivalence relation. Many works have explored their relation to metrics, since they can be interpreted as a kind of measure of similarity and this is, in fact, a dual notion to dissimilarity. Moreover, the problem of how to construct new indistinguishability fuzzy relations by means of aggregation has been explored in the literature. In this paper, we provide new characterizations of those functions that allow us to merge a collection of indistinguishability fuzzy relations into a new one in terms of triangular triplets and, in addition, we explore the relationship between such functions and those that aggregate extended pseudo-metrics, which are the natural distances associated to indistinguishability fuzzy relations. Our new results extend some already known characterizations which involve only bounded pseudo-metrics. In addition, we provide a completely new description of those indistinguishability fuzzy relations that separate points, and we show that both differ a lot.

scholarly journals Modeling the seam strength of denim garments by using fuzzy expert system

2021 ◽  
Vol 16 ◽  
pp. 155892502198897
Author(s):  
Joy Sarkar ◽  
Md Abdullah Al Faruque ◽  
Moni Sankar Mondal
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Linear Density ◽  
Unit Length ◽  
Coefficient Of Determination ◽  
Sewing Thread ◽  
External Forces ◽  
Fuzzy Logic Expert System ◽  
The Relationship ◽  
Sufficient Strength

The main purpose of this study is to predict and develop a model for forecasting the Seam Strength (SS) of denim garments with respect to the thread linear density (tex) and Stitches Per Inch (SPI) by using a Fuzzy Logic Expert System (FLES). The seam strength is an important factor for the serviceability of any garments. As seams bound the fabric pieces together in a garment, the seams must have sufficient strength to execute this property even in the unexpected severe conditions where the garments are subjected to loads or any additional internal or external forces. Sewing thread linear density and number of stitches in a unit length of the seam are the two of the most important factors that affect the seam strength of any garments. But the relationship among these two specific variables and the seam strength is complex and non-linear. As a result, a fuzzy logic based model has been developed to demonstrate the relationship among these parameters and the developed model has been validated by the experimental trial. The coefficient of determination ( R2) was found to be 0.98. The mean relative error also lies withing acceptable limit. The results have suggested a very good performance of the model in the case of the prediction of the seam strength of the denim garments.

scholarly journals Relationship of patient shame to working alliance and satisfaction: a preliminary investigation

2019 ◽  
Vol 14 (4) ◽  
pp. 251-263
Author(s):  
Daniel J. Carabellese ◽  
Michael J. Proeve ◽  
Rachel M. Roberts
Keyword(s):  
Patient Satisfaction ◽  
Working Alliance ◽  
Preliminary Investigation ◽  
Community Members ◽  
Content Type ◽  
Mediation Analyses ◽  
External Shame ◽  
Relationship Of ◽  
The Relationship

Purpose The purpose of this paper is to explore the relationship of two distinct variants of dispositional shame (internal and external shame) with collaborative, purpose-driven aspects of the patient–provider relationship (working alliance) and patient satisfaction. The aim of this research was to conduct a preliminary investigation into the relevance of dispositional shame in a general healthcare population. Design/methodology/approach In total, 127 community members (mean age 25.9 years) who reported that they had regularly seen a GP over the past year were recruited at an Australian university. Participants were asked to reflect on their relationship with their GP, and completed instruments assessing various domains of shame, as well as working alliance and patient satisfaction. Findings Non-parametric correlations were examined to determine the direction and strength of relationships, as well as conducting mediation analyses where applicable. Small, negative correlations were evident between external shame and working alliance. Both external and internal shame measures were also negatively correlated with patient satisfaction. Finally, the relationship of external shame to patient satisfaction was partially mediated by working alliance. Practical implications Both the reported quality of patient–provider working alliance, and level of patient satisfaction are related to levels of dispositional shame in patients, and working alliance may act as a mediator for this relationship. Originality/value The findings from this preliminary study suggest that internal and external shame are important factors to consider in the provision of medical care to maximise the quality of patient experience and working alliance.

MEDUSA: A Fuzzy Expert System for Medical Diagnosis of Acute Abdominal Pain

1994 ◽  
Vol 33 (05) ◽  
pp. 522-529 ◽  
Author(s):  
M. Fathi-Torbaghan ◽  
D. Meyer
Keyword(s):  
Fuzzy Logic ◽  
Abdominal Pain ◽  
Expert System ◽  
Acute Abdominal Pain ◽  
Medical Knowledge ◽  
Clinical Problem ◽  
Fuzzy Relations ◽  
Diagnostic Decision ◽  
Special Cases ◽  
Hybrid Concept

Abstract:Even today, the diagnosis of acute abdominal pain represents a serious clinical problem. The medical knowledge in this field is characterized by uncertainty, imprecision and vagueness. This situation lends itself especially to be solved by the application of fuzzy logic. A fuzzy logic-based expert system for diagnostic decision support is presented (MEDUSA). The representation and application of uncertain and imprecise knowledge is realized by fuzzy sets and fuzzy relations. The hybrid concept of the system enables the integration of rulebased, heuristic and casebased reasoning on the basis of imprecise information. The central idea of the integration is to use casebased reasoning for the management of special cases, and rulebased reasoning for the representation of normal cases. The heuristic principle is ideally suited for making uncertain, hypothetical inferences on the basis of fuzzy data and fuzzy relations.

The relationship between patient donation and satisfaction with online healthcare service quality

2019 ◽  
Vol 47 (12) ◽  
pp. 1-10
Author(s):  
Yuanrong Hu ◽  
Shengkang Lu ◽  
Zhongming Tang
Keyword(s):  
Patient Satisfaction ◽  
Healthcare Service ◽  
Outcome Quality ◽  
Healthcare Applications ◽  
Mobile Healthcare ◽  
Process And Outcome ◽  
Patient Consultation ◽  
The Impact ◽  
The Relationship

We explored how donation relates to patient satisfaction with the quality of process and outcome in an online healthcare service. Using a dataset of 496,723 patient consultation records collected from ChunyuDoctor, which is among the largest of the Chinese mobile healthcare applications, we conducted a multiple regression and found that patient satisfaction with both process and outcome jointly influenced their donation. We also found that higher quality satisfaction levels meant paying patients were more likely to donate than were free patients. Our results also showed satisfaction with the quality of the process and the outcome had an equal impact on patient donation for the free patients, but the impact of process quality was greater than that of outcome quality for the paying patients, suggesting the importance of enhancing the quality of the process in an online healthcare service. Implications of the findings are discussed.

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